Skin Disease Detection using Artificial Intelligence Algorithms

Skin disorders are more widespread than other diseases and have a significant influence on people's lives and health. Bacteria, allergies, viruses, and fungal infections, among other things, can cause skin diseases. The use of lasers and photonics has greatly improved the accuracy and speed of skin

Project Title

Skin Disease Detection using Artificial Intelligence Algorithms

Project Area of Specialization

Computer Science

Project Summary

Skin disorders are more widespread than other diseases and have a significant influence on people's lives and health. Bacteria, allergies, viruses, and fungal infections, among other things, can cause skin diseases. The use of lasers and photonics has greatly improved the accuracy and speed of skin disease diagnosis, but the cost of such diagnosis remains limited and expensive. A new study provides an effective method for identifying specific types of skin diseases. To improve the accuracy of diagnosis for multitype skin diseases, automatic approaches must be developed. A new recognition approach will be developed in this effort to distinguish between two basic classes of skin tumors: benign and malignant skin disease. The grey-level co-occurrence matrix (GLCM) approach will be used to segment skin disease images. The texture and color characteristics of various skin disease photos may be reliably determined. Finally, in this study, several forms of skin illnesses will be recognized more efficiently utilizing the convolutional neural network (CNN) classification method.

Dermatological problems are among the most common illnesses in the globe. Because of the intricacies of skin tone, color, and hair presence, identifying skin illnesses is particularly challenging. The rise of computer science and technology in the medical industry has made this easier and more possible. Skin illnesses, in general, are persistent, contagious, and can occasionally progress to skin cancer. As a result, skin disorders must be detected early in order to limit the danger of their development and spread. The diagnosis and treatment of dermatological illnesses is a time-consuming process that costs the sufferer both financially and physically. As a result, DARMA  is a web-based application that will employ Artificial Intelligence technologies to discover skin lesions while the user is sitting at home.

Previously, there were several web programs that assisted in the detection of skin problems. However, all of these applications have an unnecessary procedure and surveys that drive consumers away from these platforms. Those web apps ask a slew of inquiries, making it difficult for the user, who has already come to find a cure for the sickness but is stymied by further formalities when they arrive at the web application.

The user-friendliness of our online application will be the distinguishing feature. All users need to do is make an account and then submit a photo of their skin. The user will be alerted whether or not he or she has a sickness after the photo has been posted. If a condition is discovered, it will be classified as benign or malignant based on the skin image supplied.

Project Objectives

1. The main objective of this product development is to privilege the remote areas by installing it in the medical centers over there. So, they could also have access and afford such treatments and checkups easily.
2. We all know that dermatology is one of the expensive treatments in the field of medicine and surgery, with that, we will initiate this project mainly focusing on the friendly user interface so it could be easily operated by the individuals of all backgrounds.
3. Another motive of this project is to dissipate all the fake skin detection applications saturated over the internet claiming to be the best.
4. Our business goal is to make the system fully functional and market it to the vendors specifically to the doctors and medical field where this product will be of prominent importance. Secondly, this app will engage the mass traffic to our application to generate the revenue with the help of marketing techniques.
5. Raising public knowledge of the benefits of detection and influencing attributes and behavior towards disease detection of skin while sitting at home.

Project Implementation Method

Our project implementation has three systems that will be used to accomplish the set task. We will be designing a web-based application using HTML / CSS (depends on the need). A simple, interactive, and easy to use front-end user interface will be our priority so the application could be used effectively by all the people. With that MySQL Database will be created that will allow us to keep the user information, create backup and keep the record of images of skin uploaded by the users. This will help us in data collection and provide more precise results. In addition to that, we will be using convolutional neural network (CNN).

Convolutional Neural Network (CNN) is a class of deep neural networks, most applied to analyzing visual imagery that we will be using in our project. A Convolutional Neural Network (CNN) is a Deep Learning algorithm which can take in an input image, assign importance (learnable weights and biases) to various aspects/objects in the image and be able to differentiate one from the other.

There are some layers on which our application will be working:

Convolution Layer:

 Convolutional layer is also known as feature extractor layer because we can extract the features of the image with the help of this layer. At first, an image segment is associated with convolutional layer to perform the convolution operation. The produced output will be the input for the upcoming layer. ReLU (Rectifier Linear Unit) activation function is also the part of convolutional layer to set all negative values zero.

What is ReLU?

The rectified linear unit (ReLU) is a piecewise linear function that will show the input same as output if it is positive, otherwise, the output will be displayed as zero. For many types of neural networks, ReLU has become the default activation function because it is easier to train and often achieves better performance for the models that use it.

Pooling Layer: 

After convolution layer. we used max pooling to reduce the geometric volume of the input image. If we do not use pooling / max pooling and simply apply FC (Fully Connected) layer after convolutional layer, computationally it is very costly then, and we do not need it.

Dense Layer: 

The dense layer is the regular deeply connected neural network layer. It is the most widely recognized and often utilized layer.

Output Layer: After several padding and convolutional layers, we require the output as a class. We have the option to reduce the parameters and extract features from the original images in convolution and pooling layers. We need to apply the FC layer to produce an output equivalent to the number of classes we need. It gets extreme to arrive at that number with simply the convolution layers. Sigmoid is another activation function utilized in the output layer to generate the results.

Benefits of the Project

1. Our planned app serves as a bridge platform for several services working on the same aim. It will boost productivity and raise public understanding about how to use technology in the most effective way possible.

2. We all know that dermatology is one of the expensive treatments in the field of medicine and surgery, with that, we will initiate this project mainly focusing on the friendly user interface so it could be easily operated by the individuals of all backgrounds.

3. Another goal of this research is to get rid of all of the phony skin identification software’s that area s saturating the internet and claiming to be the finest.

4. Increasing public awareness of the benefits of skin disease detection and influencing traits and behavior toward skin disease detection while at home.

Technical Details of Final Deliverable

1.  Product Features

This project provides the user to register into the web-application. Afterwards, the user has to login to use the services of the product. In the system, an option of uploading the image is also integrated that is used to diagnose the disease from the image uploaded. We tried to provide secure and reliable platform with interactive and user-friendly functionalities.

2. Functional Description

The functional description of the system and all the functions that a system can perform are described below in this section:

There are two main classes in the system that is User and Admin.

User

All the following functions can be performed by the user in the web-application.

1) Signup:

This functionality is used by the user to sign up for the system. Otherwise, the user could not use the system.

2) Login:

This functionality is used by the user for logging in to the system and use the services provided by web-application.

3) View Profile:

This functionality helps the registered user LO view their profile in the system.

4) Edit Profile:

This functionality helps the registered user to edit their profile information if need to make any changes.

5) Delete Profile:

If any user feels not to use our system anymore, then he/she has the option to delete their registered profile. Once they delete their profile, they will be logged out wiping all their information from the system.

6) Upload Image:

Using this functionality, the registered user to is able to upload the image and obtain the results from the system.

7) Logout:

This functionality will logout the registered user from the system.

Admin

All the following functions can be performed by the admin in the web-application. in

1) Login:

This functionality is used by the admin for logging in to the system and use the web application services.

2) Manage User Profiles:

This functionality is used by the admin for managing all the registered user profiles.

3) Logout:

This functionality will logout the admin from the system.

Final Deliverable of the Project

Software System

Core Industry

IT

Other Industries

Medical

Core Technology

Artificial Intelligence(AI)

Other Technologies

Others

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com